# Packages used for the Final Project

library(countrycode)
library(tidyverse)
## ── Attaching packages ───────────────────── tidyverse 1.2.1 ──
## ✔ ggplot2 3.1.0       ✔ purrr   0.3.0  
## ✔ tibble  2.0.1       ✔ dplyr   0.8.0.1
## ✔ tidyr   0.8.2       ✔ stringr 1.4.0  
## ✔ readr   1.3.1       ✔ forcats 0.3.0
## ── Conflicts ──────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
library(readxl)
library(maps)
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##     map
library(RColorBrewer)
library(viridis)
## Loading required package: viridisLite
library(rworldmap)
## Loading required package: sp
## ### Welcome to rworldmap ###
## For a short introduction type :   vignette('rworldmap')
library(maptools)
## Checking rgeos availability: TRUE
library(dplyr)
library(ggplot2)
library(plotly) 
## 
## Attaching package: 'plotly'
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library(gifski)
library(gganimate)
#Datasets used for the Final Project

Current_USD <- read_excel('Military_Expenditure_Data.xlsx', sheet = 'Current USD') #Sipri Dataset

Share_of_GDP <- read_excel('Military_Expenditure_Data.xlsx', sheet = 'Share of GDP', skip = 5) #Sipri Dataset

Arms_Import <- read_excel('Arms_Imported.xlsx', sheet = "Data", skip = 3) #WorldBank Dataset obtained from Sipri

Military_Personal <- read_excel('Armed_Forces_Personel.xlsx', sheet = 'Data', skip = 3) #WorldBank Dataset obtained from Sipri

GlobalFirePower <- read_excel('GlobalFirePower.xlsx', sheet = 'GlobalFirePower')
#Cleaning of Datasets 
#Gathering columns and mutating values to numeric
# Datasets messy formats were all similar

Current_USD <- Current_USD %>% gather(Year, Value, -Country, -Notes) %>% mutate(Value = as.numeric(Value), Year = as.numeric(Year)) %>% filter(!is.na(Value)) %>% mutate(Value = Value)
## Warning: NAs introduced by coercion
Share_of_GDP <- Share_of_GDP %>% gather(Year, Value, -Country, -Notes) %>% mutate(Value = as.numeric(Value), Year = as.numeric(Year)) %>% filter(!is.na(Value))
## Warning: NAs introduced by coercion
Arms_Import <- Arms_Import %>% gather(Year, Value, -`Country Name`, -`Country Code`) %>% mutate(Value = as.numeric(Value), Year = as.numeric(Year)) %>% rename(Country = `Country Name`, iso3c = `Country Code`) %>% filter(!is.na(Value))
## Warning: NAs introduced by coercion

## Warning: NAs introduced by coercion
Military_Personal <- Military_Personal %>% gather(Year, Value, -`Country Name`, -`Country Code`) %>% mutate(Value = as.numeric(Value), Year = as.numeric(Year)) %>% rename(Country = `Country Name`, iso3c = `Country Code`) %>% filter(!is.na(Value)) 
## Warning: NAs introduced by coercion

## Warning: NAs introduced by coercion
#Adding missing countries and country codes 

Current_USD <- Current_USD %>% mutate(iso3c = countrycode(Country, "country.name", destination = "iso3c")) %>% mutate(iso3c = ifelse(Country == "Kosovo", "KOS", iso3c))
## Warning in countrycode(Country, "country.name", destination = "iso3c"): Some values were not matched unambiguously: Central African Rep., Czechoslovakia, Kosovo
Current_USD[Current_USD$Country == "Central African Rep.", "iso3c"] <- "CAF"

Current_USD[Current_USD$Country == "South Sudan", "iso3c"] <- "SSD"

Share_of_GDP <- Share_of_GDP %>% mutate(iso3c = countrycode(Country, "country.name", destination = "iso3c")) %>% mutate(iso3c = ifelse(Country == "Kosovo", "KOS", iso3c))
## Warning in countrycode(Country, "country.name", destination = "iso3c"): Some values were not matched unambiguously: Central African Rep., Kosovo
Share_of_GDP[Share_of_GDP$Country == "Central African Rep.", "iso3c"] <- "CAF" # Adding
#We are using a large GeoSpatialDataframe to Plot Countires and their information
#Libraries we will use for this
#Loading Geo_spatial Data Frame created @ https://geojson-maps.ash.ms/
library(broom)
library(geojsonio)
## 
## Attaching package: 'geojsonio'
## The following object is masked from 'package:base':
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##     pretty
world_map <-  geojsonio::geojson_read('custom.geo.json', what = 'sp')


world_map <- tidy(world_map, region = "sov_a3") # Changing from large spatial dataframe to regular data frame.
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
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## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
world_map <- world_map %>% mutate(iso3c = id)

#Adding ISO
#Manual searched for incorrect country codes and fixed them to match
world_map[world_map$id == "US1", "iso3c"] <- "USA"
world_map[world_map$id == "CH1", "iso3c"] <- "CHN"
world_map[world_map$id == "AU1", "iso3c"] <- "AUS"
world_map[world_map$id == "DN1", "iso3c"] <- "DNK"
world_map[world_map$id == "FI1", "iso3c"] <- "FIN"
world_map[world_map$id == "FR1", "iso3c"] <- "FRA"
world_map[world_map$id == "GB1", "iso3c"] <- "GBR"
world_map[world_map$id == "NL1", "iso3c"] <- "NLD"
world_map[world_map$id == "NZ1", "iso3c"] <- "NZL"
world_map[world_map$id == "SDS", "iso3c"] <- "SSD"
world_map[world_map$id == "SOL", "iso3c"] <- "SOM"
world_map[world_map$id == "SAH", "iso3c"] <- "MAR"
#North Korea, The Bahamas, Bhutan, suriname are the only missing and not reported.

#Practice Plot
world_map %>% ggplot(aes(x = long, y = lat, group = group))+ geom_polygon()

#Statistical Plots 
#We are going to do some exploratory Visualization 

#Comparing top Militaries Spending
Current_USD %>% group_by(Country, iso3c, Year, Value) %>% filter(Year >= 1992) %>% filter(Country %in% c("USA", "Russian Federation", "China, P.R.", "India", "France")) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country)) + ggtitle("Military Expenditure Country USD")+ xlab("Years")+ ylab("Current Prices")+scale_x_continuous(breaks = c(1992:2017))+ scale_y_continuous(breaks = c(0e+00, 2e+05, 4e+05, 6e+05), labels = c("Hundreds of Millions", "200 Billion", "400 Billion", "600 Billion"))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))

Current_USD %>% group_by(Country, iso3c, Year, Value) %>% filter(Year >= 1992) %>% filter(Country %in% c("USA", "Russian Federation", "China, P.R.", "India", "France")) %>% ggplot(aes(x = Year, y = log2(Value)))+ geom_line(aes(color = Country)) + ggtitle("Military Expenditure Country USD")+ xlab("Years")+ ylab("Current Prices Log2")+scale_x_continuous(breaks = c(1992:2017))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))

#Comparing weak military Spending

Current_USD %>% group_by(Country, iso3c, Year, Value) %>% filter(Year >= 1992) %>% filter(Country %in% c("Ireland", "Sierra Leone", "Ghana", "Latvia", "Estonia")) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country)) + ggtitle("Military Expenditure(Weak) Country USD")+ xlab("Year")+ ylab("Current Prices")+scale_x_continuous(breaks = c(1992:2017))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))+ scale_y_continuous(breaks = c(0, 500, 1000, 1500), labels = c("10s of Millions", "500 Million", "1 Billion", "1.5 Billion"))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))

Current_USD %>% group_by(Country, iso3c, Year, Value) %>% filter(Year >= 1992) %>% filter(Country %in% c("Ireland", "Sierra Leone", "Ghana", "Latvia", "Estonia")) %>% ggplot(aes(x = Year, y = log2(Value)))+ geom_line(aes(color = Country)) + ggtitle("Military Expenditure(Weak) Country USD")+ xlab("Year")+ ylab("Current Prices Log2")+scale_x_continuous(breaks = c(1992:2017))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))

#------------------------------------------------------------------------#

#Comparing top Militaries Spending based on GDP
Share_of_GDP %>% group_by(Country, iso3c, Year, Value) %>% filter(Year >= 1992) %>% filter(Country %in% c("USA", "Russian Federation", "China, P.R.", "India", "France")) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country))+ ggtitle("Military Expenditure as % of GDP")+ xlab("Year")+ ylab("Military Expenditure")+ scale_y_continuous(labels = scales::percent)+scale_x_continuous(breaks = c(1992:2017))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))

#Comparing weak Militaries Spending based on GDP
Share_of_GDP %>% group_by(Country, iso3c, Year, Value) %>% filter(Year >= 1992) %>% filter(Country %in% c("Ireland", "Sierra Leone", "Ghana", "Latvia", "Estonia")) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country))+ ggtitle("Military Expenditure as % of GDP")+ xlab("Year")+ ylab("Military Expenditure")+ scale_y_continuous(labels = scales::percent)+scale_x_continuous(breaks = c(1992:2017))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))

#------------------------------------------------------------------------#

#Comparing Top Countries Military Personal

Military_Personal %>% subset(Country %in% c("United States", "Russian Federation", "China", "India", "France")) %>% filter(Year >= 1992) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country))+scale_x_continuous(breaks = c(1992:2016))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))+ggtitle("Military Personal % of Labor Force")+ xlab("Years")+ ylab("Military Personal")

#Comparing Weak Countries Military Personal
Military_Personal %>% subset(Country %in% c("Ireland", "Sierra Leone", "Ghana", "Latvia", "Estonia")) %>% filter(Year >= 1992) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country))+scale_x_continuous(breaks = c(1992:2016))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))+ggtitle("Military Expenditure as % Labor Force")+ xlab("Years")+ ylab("Military Personal")  

#------------------------------------------------------------------------#

#Comparing top Militaries Arm imports
Arms_Import %>% subset(Country %in% c("United States", "Russian Federation", "China", "India", "France")) %>% filter(Year >= 1992) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country))+ ggtitle("Military Arms Import")+ xlab("Year")+ ylab("Military Arms")+scale_x_continuous(breaks = c(1992:2016))+ scale_y_continuous(breaks = c(2.000e+06, 1.029e+09, 2.500e+09, 5.322e+09), labels = c("2 Million", "1 Billion", "2.5 Billion", "5 Billion"))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1)) #Number of Arm imports for each powerful Country

#Comparing Weak Militaries Arm imports
Arms_Import %>% subset(Country %in% c("Ireland", "Sierra Leone", "Ghana", "Latvia", "Estonia")) %>% filter(Year >= 1992) %>% ggplot(aes(x = Year, y = Value))+ geom_line(aes(color = Country))+ ggtitle("Military Arms Import")+ xlab("Year")+ ylab("Military Arms")+scale_x_continuous(breaks = c(1992:2016))+ scale_y_continuous(breaks = c(2.000e+06, 15.000e+06, 38.000e+06, 76.000e+06), labels = c("2 Million", "15 Million", "38 Million", "76 Million"))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1)) #Number of Arm imports for each powerful Country

#------------------------------------------------------------------------#

#Countries Military Arsenals for Year 2017
#Statistic

GlobalFirePower_X<- GlobalFirePower %>% select(Country, ISO3, `Total Aircraft Strength`, `Total Helicopter Strength`, `Combat Tanks`, 19, 20, 23)

GlobalFirePower_X %>% filter(Country %in% c("United States", "Russia", "China", "India", "France")) %>% summary()
##    Country              ISO3           Total Aircraft Strength
##  Length:5           Length:5           Min.   : 1305          
##  Class :character   Class :character   1st Qu.: 2102          
##  Mode  :character   Mode  :character   Median : 2955          
##                                        Mean   : 4784          
##                                        3rd Qu.: 3794          
##                                        Max.   :13762          
##  Total Helicopter Strength  Combat Tanks   Armored Fighting Vehicles
##  Min.   : 610              Min.   :  406   Min.   : 4788            
##  1st Qu.: 666              1st Qu.: 4426   1st Qu.: 6704            
##  Median : 912              Median : 5884   Median : 6863            
##  Mean   :1928              Mean   : 7478   Mean   :18143            
##  3rd Qu.:1389              3rd Qu.: 6457   3rd Qu.:31298            
##  Max.   :6065              Max.   :20216   Max.   :41062            
##  Self-Propelled Artillery Total Naval Assets
##  Min.   : 290             Min.   :118.0     
##  1st Qu.: 325             1st Qu.:295.0     
##  Median :1710             Median :352.0     
##  Mean   :2046             Mean   :378.8     
##  3rd Qu.:1934             3rd Qu.:415.0     
##  Max.   :5972             Max.   :714.0
GlobalFirePower_X %>% filter(Country %in% c("Ireland", "Sierra Leone", "Ghana", "Latvia", "Estonia")) %>% summary()
##    Country              ISO3           Total Aircraft Strength
##  Length:4           Length:4           Min.   : 4.00          
##  Class :character   Class :character   1st Qu.: 4.75          
##  Mode  :character   Mode  :character   Median : 5.50          
##                                        Mean   :10.00          
##                                        3rd Qu.:10.75          
##                                        Max.   :25.00          
##  Total Helicopter Strength  Combat Tanks Armored Fighting Vehicles
##  Min.   : 4.00             Min.   :0.0   Min.   : 10.0            
##  1st Qu.: 4.00             1st Qu.:0.0   1st Qu.:190.0            
##  Median : 4.50             Median :0.0   Median :275.0            
##  Mean   : 6.75             Mean   :0.5   Mean   :219.5            
##  3rd Qu.: 7.25             3rd Qu.:0.5   3rd Qu.:304.5            
##  Max.   :14.00             Max.   :2.0   Max.   :318.0            
##  Self-Propelled Artillery Total Naval Assets
##  Min.   :0                Min.   : 6.0      
##  1st Qu.:0                1st Qu.: 9.0      
##  Median :0                Median :14.0      
##  Mean   :0                Mean   :13.5      
##  3rd Qu.:0                3rd Qu.:18.5      
##  Max.   :0                Max.   :20.0
#Mexico Information

Current_USD %>% group_by(Country, iso3c, Year, Value) %>% filter(Country == "Mexico") %>% filter(Year >= 1970) %>% ggplot(aes(x = Year, y = Value))+ geom_point()+ geom_line()+ ggtitle("Mexico's Military Expenditure")+ xlab("Year")+ ylab("Current Prices")+ scale_y_continuous(breaks = c(0, 2500, 5000, 7500), labels = c("Hundreds of Millions", "2.5 Billion", "5 Billion", "7.5 Billion"))

#-----------------------------------------------------------------------------------------------------#
Share_of_GDP %>% group_by(Country, iso3c, Year, Value) %>% filter(Country == "Mexico") %>% filter(Year >= 1970) %>% ggplot(aes(x = Year, y = Value * 100))+ geom_point()+ geom_line()+ ggtitle("Mexico's Military Expenditure as % of GDP")+ xlab("Year")+ ylab("Percent of GDP")+scale_y_continuous(breaks = c(.400, .500, .600, .700), labels = c("4%", "5%", "6%", "7%"))

#-----------------------------------------------------------------------------------------------------#
Military_Personal %>% filter(Country == "Mexico") %>% filter(Year >= 1970) %>% ggplot(aes(x = Year, y = Value))+ geom_point()+ geom_line()+
  ggtitle("Mexico's Military Personal as % of Labor Force")+ xlab("Year")+ ylab("Military Personal")+ scale_y_continuous(breaks = c(.45, .50, .55, .60, .65), labels = c(".45%", ".50%", ".55%", ".60%", ".65%"))# Really good graph show mexicos military increase as a percent of labor force

#-----------------------------------------------------------------------------------------------------#
Arms_Import %>% filter(Country == "Mexico") %>% filter(Year >= 1970) %>% ggplot(aes(x = Year, y = Value))+ geom_point()+ geom_line()+
   ggtitle("Mexico's Military Arms Import")+ xlab("Year")+ ylab("Military Arms")+ scale_y_continuous(breaks = c(0e+00, 1e+08, 2e+08, 3e+08, 4e+08, 5e+08), labels = c("6 Million", "100 Million", "200 Million", "300 Million", "400 Million", "500 Million"))+ theme(axis.text.x = element_text(angle = 80, vjust = 1, hjust = 1))

#-----------------------------------------------------------------------------------------------------#
GlobalFirePower_X<- GlobalFirePower %>% select(Country, ISO3, `Total Aircraft Strength`, `Total Helicopter Strength`, `Combat Tanks`, 19, 20, 23)

GlobalFirePower_X %>% filter(Country == "Mexico")
## # A tibble: 1 x 8
##   Country ISO3  `Total Aircraft… `Total Helicopt… `Combat Tanks`
##   <chr>   <chr>            <dbl>            <dbl>          <dbl>
## 1 Mexico  MEX                452              209              0
## # … with 3 more variables: `Armored Fighting Vehicles` <dbl>,
## #   `Self-Propelled Artillery` <dbl>, `Total Naval Assets` <dbl>
#Current USD
data_for_map <- Current_USD %>% group_by(Country) %>% filter(Year == max(Year))

world_map_join <- world_map %>% left_join(data_for_map, by = "iso3c")

Flat_Map <- world_map_join %>% ggplot(aes(x = long, y = lat, group = group, fill = log2(Value)))+
  geom_polygon() + scale_fill_viridis(option = "inferno", direction = -1)

Flat_Map 

#______________________________________________________________________________#

data_for_map_gdp <- Share_of_GDP %>% group_by(Country) %>% filter(Year == max(Year))

world_map_join_gdp <- world_map %>% left_join(data_for_map_gdp, by = "iso3c")

Flat_Map_gdp <- world_map_join_gdp %>% ggplot(aes(x = long, y = lat, group = group, fill = log2(Value)))+
  geom_polygon()+ scale_fill_viridis(option = "inferno", direction = -1)

Flat_Map_gdp

#Current USD
Animation_Prep <- Current_USD %>% group_by(Country)
Animation_Prep_2 <- Share_of_GDP %>% group_by(Country)



Animation_Map <- world_map %>% left_join(Animation_Prep, by = "iso3c") %>% filter(Year >= 1992)
Animation_Map_2 <- world_map %>% left_join(Animation_Prep_2, by = "iso3c") %>% filter(Year >= 1992)
#Animation_Map <- na.omit(Animation_Map)

Animation <- ggplot() + geom_polygon(data = world_map, aes(x = long, y = lat, group = group))+
  geom_polygon(data = Animation_Map, aes(x = long, y = lat, group = group, fill = sqrt(Value)))+ theme(legend.position = "top")+
  scale_fill_viridis(option = "viridis", direction = -1)+ labs(title = "World Map USD Year: {frame_time}")+
  transition_time(Year, range = c(1992, 2017)) + ease_aes('linear') 


AnimationX <- ggplot() + geom_polygon(data = world_map, aes(x = long, y = lat, group = group))+
  geom_polygon(data = Animation_Map_2, aes(x = long, y = lat, group = group, fill = sqrt(Value)))+  theme(legend.position = "top")+
  scale_fill_viridis(option = "inferno", direction = -1)+ labs(title = "World Map GDP Year: {frame_time}")+
  transition_time(Year, range = c(1992, 2017)) + ease_aes('linear')
#Plot1 <-  animate(Animation) 
#anim_save("Expenditure.gif", Plot1 )
#Plot2 <- animate(AnimationX)
#anim_save("GDP.gif", Plot2 )